Difference between revisions of "10-601 DR"
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| + | This a lecture used in the [[Syllabus for Machine Learning 10-601 in Fall 2014]] | ||
| + | |||
| + | |||
=== Slides === | === Slides === | ||
| − | [http://curtis.ml.cmu.edu/w/courses/images/ | + | [http://curtis.ml.cmu.edu/w/courses/images/a/a7/Lecture14-clustering.pdf Slides in PDF] |
=== Readings === | === Readings === | ||
| − | + | Bishop's Chapter 9 | |
| − | + | ||
| − | * | + | Mitchell 6.12 also has a nice description of EM and k-means. |
| − | ** | + | |
| − | ** | + | === What You Should Know Afterward === |
| + | |||
| + | * Linkage methods | ||
| + | * Bottom up vs. top down clustering | ||
| + | * Run time of different clustering methods | ||
| + | * Assumptions, advntages and disadvantages of each method | ||
| + | * (optional) Optimal leaf ordering | ||
| + | * (optional) Spectral clustering | ||
| + | * (optional) Self organizing maps | ||
Latest revision as of 10:08, 12 August 2014
This a lecture used in the Syllabus for Machine Learning 10-601 in Fall 2014
Slides
Readings
Bishop's Chapter 9
Mitchell 6.12 also has a nice description of EM and k-means.
What You Should Know Afterward
- Linkage methods
- Bottom up vs. top down clustering
- Run time of different clustering methods
- Assumptions, advntages and disadvantages of each method
- (optional) Optimal leaf ordering
- (optional) Spectral clustering
- (optional) Self organizing maps
